Clinical Genomics provides an overview of the various next-generation sequencing (NGS) technologies that are currently used in clinical diagnostic laboratories. It presents key bioinformatic challenges and the solutions that must be addressed by clinical genomicists and genomic pathologists, such as specific pipelines for identification of the full range of variants that are clinically important. This book is also focused on the challenges of diagnostic interpretation of NGS results in a clinical setting. Its final sections are devoted to the emerging regulatory issues that will govern clinical use of NGS, and reimbursement paradigms that will affect the way in which laboratory professionals get paid for the testing. Simplifies complexities of NGS technologies for rapid education of clinical genomicists and genomic pathologists towards genomic medicine paradigm Tried and tested practice-based analysis for precision diagnosis and treatment plans Specific pipelines and meta-analysis for full range of clinically important variants

Over the past 50 years, scientists have made incredible progress in the application of genetic research to human health care and disease treatment. Innovative tools and techniques, including gene therapy and CRISPR-Cas9 editing, can treat inherited disorders that were previously untreatable, or prevent them from happening in the first place. You can take a DNA test to learn where your ancestors are from. Police officers can use genetic evidence to identify criminals—or innocents. And some doctors are using new medical techniques for unprecedented procedures. Genomics: A Revolution in Health and Disease Discovery delves into the history, science, and ethics behind recent breakthroughs in genetic research. Authors Whitney Stewart and Hans Andersson, MD, present fascinating case studies that show how real people have benefitted from genetic research. Though the genome remains full of mysteries, researchers and doctors are working hard to uncover its secrets and find the best ways to treat patients and cure diseases. The discoveries to come will inform how we target disease treatment, how we understand our health, and how we define our very identities.

Genomics and Society; Ethical, Legal-Cultural, and Socioeconomic Implications is the first book to address the vast and thorny web of ELSI topics identified as core priorities of the NHGRI in 2011. The work addresses fundamental issues of biosociety and bioeconomy as the revolution in biology moves from research lab to healthcare system. Of particular interest to healthcare practitioners, bioethicists, and health economists, and of tangential interest to the gamut of applied social scientists investigating the societal impact of new medical paradigms, the work describes a myriad of issues around consent, confidentiality, rights, patenting, regulation, and legality in the new era of genomic medicine. Addresses the vast and thorny web of ELSI topics identified as core priorities of the NHGRI in 2011 Presents the core fundamental issues of biosociety and bioeconomy as the revolution in biology moves from research lab to healthcare system Describes a myriad of issues around consent, including confidentiality, rights, patenting, regulation, and more

Medical and Health Genomics provides concise and evidence-based technical and practical information on the applied and translational aspects of genome sciences and the technologies related to non-clinical medicine and public health. Coverage is based on evolving paradigms of genomic medicine—in particular, the relation to public and population health genomics now being rapidly incorporated in health management and administration, with further implications for clinical population and disease management. Provides extensive coverage of the emergent field of health genomics and its huge relevance to healthcare management Presents user-friendly language accompanied by explanatory diagrams, figures, and many references for further study Covers the applied, but non-clinical, sciences across disease discovery, genetic analysis, genetic screening, and prevention and management Details the impact of clinical genomics across a diverse array of public and community health issues, and within a variety of global healthcare systems

Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.

Researchers in the field of ecological genomics aim to determine how a genome or a population of genomes interacts with its environment across ecological and evolutionary timescales. Ecological genomics is trans-disciplinary by nature. Ecologists have turned to genomics to be able to elucidate the mechanistic bases of the biodiversity their research tries to understand. Genomicists have turned to ecology in order to better explain the functional cellular and molecular variation they observed in their model organisms. We provide an advanced-level book that covers this recent research and proposes future development for this field. A synthesis of the field of ecological genomics emerges from this volume. Ecological Genomics covers a wide array of organisms (microbes, plants and animals) in order to be able to identify central concepts that motivate and derive from recent investigations in different branches of the tree of life. Ecological Genomics covers 3 fields of research that have most benefited from the recent technological and conceptual developments in the field of ecological genomics: the study of life-history evolution and its impact of genome architectures; the study of the genomic bases of phenotypic plasticity and the study of the genomic bases of adaptation and speciation.

In 2001 the Human Genome Project succeeded in mapping the DNA of humans. This landmark accomplishment launched the field of genomics, the integrated study of all the genes in the human body and the related biomedical interventions that can be tailored to benefit a person's health. Today genomics, part of a larger movement toward personalized medicine, is poised to revolutionize health care. By cross-referencing an individual's genetic sequence -- their genome -- against known elements of "Big Data," elements of genomics are already being incorporated on a widespread basis, including prenatal disease screening and targeted cancer treatments. With more innovations soon to arrive at the bedside, the promise of the genomics revolution is limitless. This entry in the What Everyone Needs to Know series offers an authoritative resource on the prospects and realities of genomics and personalized medicine. As this science continues to alter traditional medical paradigms, consumers are faced with additional options and more complicated decisions regarding their health care. This book provides the essential information everyone needs.